
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "13"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 120 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 115 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	75.844308	85.396631	124.192222	158.303160	21.252721	43.882110	50.274353	117.459910	0.0191	0.0174	0.0016	1.154778	1.129189
2459593	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	229.572329	62.365174	167.885431	170.394488	37.638002	64.817224	114.934664	212.696392	0.0199	0.0184	0.0010	1.147271	1.123807
2459592	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	27.952420	7.236367	66.945998	60.372271	42.552548	76.666813	92.353259	99.556312	0.0206	0.0194	0.0020	nan	nan
2459591	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	203.030713	64.160887	172.203390	188.717989	32.651499	45.359667	169.496098	261.046627	0.0199	0.0177	0.0015	1.140939	1.099989
2459590	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	289.682733	129.284529	181.147575	181.590347	34.557540	45.302002	185.995822	280.721799	0.0183	0.0183	0.0007	1.103813	1.073986
2459589	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	332.156485	344.458447	inf	inf	20.748426	56.006438	92.714305	403.800624	nan	nan	nan	0.000000	0.000000
2459588	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	192.514457	56.441008	231.123516	208.970768	23.319309	47.376839	57.881871	86.209418	0.0180	0.0176	0.0006	1.182892	1.162021
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	280.583105	136.241921	283.136680	331.034707	24.764808	83.416799	231.275102	576.479633	nan	nan	nan	0.000000	0.000000
2459586	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	309.497777	321.168281	inf	inf	11.435410	11.606944	282.745116	595.932439	nan	nan	nan	0.000000	0.000000
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	122.833165	56.716809	48.369715	39.698924	23.165399	9.215726	541.161707	536.178389	0.0195	0.0179	0.0010	0.000000	0.000000
2459584	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	111.910167	115.911927	262.512359	271.115937	38.553746	38.769663	137.845324	191.447542	0.0193	0.0172	0.0013	1.125000	1.117698
2459583	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459582	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	66.466895	57.070220	75.419242	79.468732	40.614108	64.613302	292.378567	446.922125	0.0189	0.0168	0.0020	1.141327	1.139137
2459581	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	83.178195	91.420893	83.952540	77.595617	33.828002	29.627638	314.244683	294.032596	0.0191	0.0175	0.0014	1.111037	1.111733
2459580	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	47.794351	50.680396	69.265414	72.362819	25.967958	30.317617	120.468324	211.962719	0.0192	0.0181	0.0008	1.119220	1.115590
2459579	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	79.385483	72.234569	99.758454	98.790281	51.954116	45.979249	501.802650	612.342366	0.0186	0.0172	0.0007	1.137421	1.136164
2459578	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	8.528740	9.494009	39.631482	45.403102	201.310090	288.652319	1081.565241	1549.219467	0.0191	0.0173	0.0012	nan	nan
2459577	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	64.147712	89.541208	69.822173	86.380988	38.214398	56.851619	225.481503	409.336963	0.0196	0.0169	0.0017	1.108682	1.099208
2459576	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	68.668103	100.541617	58.618097	68.258442	35.288819	51.858380	318.713136	512.017155	0.0189	0.0169	0.0014	0.000000	0.000000
2459575	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	40.393147	44.607950	55.898523	54.445814	17.391380	27.979609	28.549012	39.703116	0.0192	0.0182	0.0007	0.940969	0.937000
2459574	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	53.242357	52.974914	54.439900	54.076624	34.056923	46.744529	163.158970	219.551070	0.0188	0.0174	0.0011	0.755187	0.753174
2459573	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	59.217527	68.103455	92.740225	94.596706	37.313325	46.107993	277.331315	390.408352	0.0190	0.0175	0.0006	0.000000	0.000000
2459572	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	51.880201	82.119374	52.838585	64.884089	35.588434	55.757887	440.089693	941.643792	0.0184	0.0172	0.0012	0.687707	0.000000
2459571	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	8.082393	7.035758	43.233165	37.713960	177.854882	248.178440	1073.169956	1424.111620	0.0187	0.0179	0.0007	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	97.340809	89.025299	80.435813	83.010817	15.836865	28.584862	450.487088	668.885543	0.0184	0.0171	0.0009	0.000000	0.000000
2459569	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	81.785021	56.947130	82.846948	69.436252	27.870334	22.816443	46.831990	34.003511	0.0181	0.0174	0.0005	1.029952	1.032448
2459566	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	76.892531	53.819208	80.261288	73.653008	36.959873	37.467369	194.548037	197.099308	0.0192	0.0173	0.0016	0.000000	0.000000
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	0.674491	0.674491	0.714579	0.714579	1.371796	1.371796	0.680147	0.680147	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	114.515426	78.239143	89.483493	86.834479	12.746342	11.940096	273.597817	312.064164	0.0181	0.0170	0.0007	1.119990	1.119540
2459563	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	77.407138	61.344762	150.070872	142.824288	38.343583	39.368977	332.483035	308.593412	0.0189	0.0177	0.0007	0.966201	0.957847
2459562	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459561	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	49.313168	47.680246	37.418942	37.237202	10.443048	10.599533	299.262545	381.921881	0.0182	0.0173	0.0010	1.106387	1.107012
2459560	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	39.471013	43.028502	34.808808	36.630474	5.173903	7.542437	181.599409	228.152150	0.0192	0.0174	0.0018	1.123156	1.124336
2459559	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459558	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	59.666323	88.346100	73.481465	92.175535	37.683296	64.947538	269.639871	669.503793	0.0195	0.0167	0.0016	1.149363	1.137873
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0186	0.0178	0.0007	nan	nan
2459556	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	68.293307	83.502906	81.502154	89.007694	27.056077	54.023388	527.532139	1018.195703	0.0184	0.0171	0.0008	1.159739	1.155024
2459554	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0181	0.0170	0.0006	nan	nan
2459553	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0176	0.0173	0.0006	nan	nan
2459552	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	77.683248	85.535977	117.654103	130.466139	68.178818	75.538828	476.096776	621.805511	0.0185	0.0168	0.0011	0.993703	0.000000
2459551	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459550	RF_maintenance	-	99.18%	99.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0248	0.0242	0.0005	nan	nan
2459549	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	72.099718	97.520936	88.130374	96.218778	42.682841	44.275418	395.429349	489.953389	0.0185	0.0172	0.0009	1.121003	1.117356
2459542	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	127.415885	80.477554	200.466897	167.269367	4.922419	5.446206	343.311095	389.012838	0.0177	0.0173	0.0004	1.117312	1.119115
2459541	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.983141	10.624916	46.458418	47.283317	695.407300	727.524559	23.213928	20.625537	0.0186	0.0168	0.0017	1.081550	1.074414
2459540	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	75.810605	56.772077	41.258199	38.793013	17.136570	22.930898	132.194861	157.473182	0.0185	0.0173	0.0006	1.162395	1.160670
2459536	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	197.343940	135.400408	176.226147	176.529732	71.284776	91.376029	912.808372	1238.738513	0.0180	0.0166	0.0009	1.130152	1.126494
2459535	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	109.141796	83.186202	49.027844	47.414497	42.719910	36.709063	353.245575	401.433979	0.0175	0.0169	0.0003	1.126618	1.126024
2459534	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	43.796530	38.464528	33.831092	30.422742	14.639149	11.592790	171.012000	127.983606	0.0183	0.0181	0.0006	1.144554	1.146003
2459533	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	54.957472	59.756670	71.463586	72.784141	25.231899	34.705029	300.564119	394.738425	0.0185	0.0181	0.0009	1.163844	1.157045
2459532	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	67.582061	128.252015	96.378628	135.449227	50.043927	75.475247	258.641059	650.417865	0.0189	0.0168	0.0014	1.156525	1.144876
2459530	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	46.251926	74.500113	33.371508	43.893310	14.180686	41.206792	192.344826	587.434453	0.0186	0.0169	0.0015	1.133863	1.126668
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	68.456359	71.463859	113.753112	134.936089	84.096931	187.409007	192.047804	526.940901	0.0188	0.0167	0.0016	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	108.543839	93.499597	124.918740	125.306704	91.577701	108.456454	463.894928	711.025226	nan	nan	nan	1.461965	1.468249
2459522	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	112.525326	82.169082	137.628500	131.463138	156.785264	187.857484	776.015265	871.367410	0.0189	0.0172	0.0008	1.122038	1.108737
2459513	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	9.578829	10.965954	39.183633	48.795428	225.678695	350.046843	775.636055	1508.427585	0.0204	0.0175	0.0019	nan	nan
2459508	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	84.211009	93.671027	118.084923	136.551560	46.712752	80.406044	72.567850	164.680985	0.0188	0.0165	0.0014	0.000000	0.000000
2459505	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	123.611691	79.674227	120.045968	109.854646	103.478816	131.941147	611.698779	683.803606	0.0112	0.0094	0.0048	1.089163	1.090148
2459503	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	100.548769	114.482069	182.155072	221.074852	58.300319	81.725484	401.234370	947.741472	0.0091	0.0065	0.0097	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 13 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 13, Node 0:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 13: 2459646

Antenna 13: 2459645

Antenna 13: 2459642

Antenna 13: 2459640

Antenna 13: 2459639

Antenna 13: 2459638

Antenna 13: 2459637

Antenna 13: 2459636

Antenna 13: 2459635

Antenna 13: 2459634

Antenna 13: 2459633

Antenna 13: 2459632

Antenna 13: 2459631

Antenna 13: 2459630

Antenna 13: 2459629

Antenna 13: 2459628

Antenna 13: 2459627

Antenna 13: 2459626

Antenna 13: 2459625

Antenna 13: 2459624

Antenna 13: 2459623

Antenna 13: 2459622

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Antenna 13: 2459620

Antenna 13: 2459619

Antenna 13: 2459618

Antenna 13: 2459617

Antenna 13: 2459616

Antenna 13: 2459615

Antenna 13: 2459614

Antenna 13: 2459613

Antenna 13: 2459612

Antenna 13: 2459611

Antenna 13: 2459610

Antenna 13: 2459609

Antenna 13: 2459608

Antenna 13: 2459607

Antenna 13: 2459605

Antenna 13: 2459604

Antenna 13: 2459603

Antenna 13: 2459602

Antenna 13: 2459598

Antenna 13: 2459597

Antenna 13: 2459596

Antenna 13: 2459595

Antenna 13: 2459594

Antenna 13: 2459593

Antenna 13: 2459592

Antenna 13: 2459591

Antenna 13: 2459590

Antenna 13: 2459589

Antenna 13: 2459588

Antenna 13: 2459587

Antenna 13: 2459586

Antenna 13: 2459585

Antenna 13: 2459584

Antenna 13: 2459583

Antenna 13: 2459582

Antenna 13: 2459581

Antenna 13: 2459580

Antenna 13: 2459579

Antenna 13: 2459578

Antenna 13: 2459577

Antenna 13: 2459576

Antenna 13: 2459575

Antenna 13: 2459574

Antenna 13: 2459573

Antenna 13: 2459572

Antenna 13: 2459571

Antenna 13: 2459570

Antenna 13: 2459569

Antenna 13: 2459566

Antenna 13: 2459565

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶